A Visual Servoing System for an Amphibious Legged Robot
Vision-based Robotics and Control in Natural Underwater Environments
(Sprache: Englisch)
We present a visual servoing system for an amphibious legged robot. This is a monocular-vision based servoing mechanism that enables the robot to track and follow a target both underwater and on the ground. We use three different tracking algorithms to...
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We present a visual servoing system for an amphibious legged robot. This is a monocular-vision based servoing mechanism that enables the robot to track and follow a target both underwater and on the ground. We use three different tracking algorithms to track and localize the target in the image, with color being the tracked feature. Tracking is performed based on the color of the target object, target color distribution and color distribution with a probabilistic kernel. Output from the tracker is channeled to a proportional-integral-derivative controller, which generates steering commands for the robot controller. The robot controller in turn takes the steering commands and generates motor commands for the six legs of the robot. A large class of significant applications can be addressed by allowing such a robot to follow a diver or some other moving target. The system has been evaluated in open-water environments and under natural lighting conditions, and has successfully performed tracking and following of a wide variety of target objects.
Autoren-Porträt von Junaed Sattar
Sattar, JunaedJunaed Sattar is a PhD candidate at McGill University in Montreal, Quebec, Canada. He is pursuing research in vision-based human-robot interaction and autonomous behavior. His work focuses on vision algorithms development for mobile robots, followed by extensive validation on board robotic platforms, specifically the Aqua amphibious legged robot.
Bibliographische Angaben
- Autor: Junaed Sattar
- 2008, 96 Seiten, Maße: 15 x 22 cm, Kartoniert (TB), Englisch
- Verlag: VDM Verlag Dr. Müller e.K.
- ISBN-10: 3639014332
- ISBN-13: 9783639014334
Sprache:
Englisch
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